For guidance, examples, and limits, see [Upsert data](/guides/index-data-upsert-data).

```python Python theme={null}
# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
index = pc.Index("docs-example")

upsert_response = index.upsert(
    vectors=[
        {
            "id": "vec1",
            "values": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
            "sparse_values": {
                "indices": [1, 5],
                "values": [0.5, 0.5]
            },
            "metadata": {
                "genre": "drama"
            }
        },
        {
            "id": "vec2",
            "values": [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
            "sparse_values": {
                "indices": [5, 6],
                "values": [0.4, 0.5]
            },
            "metadata": {
                "genre": "action"
            }
        }
    ],
    namespace="example-namespace"
)
```

```javascript JavaScript theme={null}
// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({ apiKey: "YOUR_API_KEY" })
const index = pc.index("docs-example")

await index.namespace('example-namespace').upsert([
  {
    id: 'vec1',
    values: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
    sparseValues: {
        indices: [1, 5],
        values: [0.5, 0.5]
    },
    metadata: {'genre': 'drama'},
  },
  {
    id: 'vec2',
    values: [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
    metadata: {'genre': 'action'},
    sparseValues: {
        indices: [5, 6],
        values: [0.4, 0.5]
    }
  }
])
```

```java Java theme={null}
import com.google.protobuf.Struct;
import com.google.protobuf.Value;
import io.pinecone.clients.Index;
import io.pinecone.clients.Pinecone;

import java.util.Arrays;
import java.util.List;

public class UpsertExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
        String indexName = "docs-example";
        Index index = pc.getIndexConnection(indexName);
        List<Float> values1 = Arrays.asList(0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f);
        List<Float> values2 = Arrays.asList(0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.9f);
        Struct metaData1 = Struct.newBuilder()
                .putFields("genre", Value.newBuilder().setStringValue("drama").build())
                .build();
        Struct metaData2 = Struct.newBuilder()
                .putFields("genre", Value.newBuilder().setStringValue("action").build())
                .build();

        index.upsert("A", values1, null, null, metaData1, null);
        index.upsert("B", values2, null, null, metaData2, null);
    }
}
```

```shell curl theme={null}
PINECONE_API_KEY="YOUR_API_KEY"
INDEX_HOST="INDEX_HOST"

curl "https://$INDEX_HOST/vectors/upsert" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Pinecone-Api-Version: 2024-04" \
  -d '{
        "vectors": [
          {
            "id": "vec1",
            "values": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
            "sparseValues": {
              "indices": [2, 7],
              "values": [0.4, 0.5]
            },
            "metadata": {
              "genre": "drama"
            }
          },
          {
            "id": "vec2",
            "values": [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
            "sparseValues": {
              "indices": [1, 4],
              "values": [0.1, 0.2]
            },
            "metadata": {
              "genre": "action"
            }
          }
        ]
      }'
```

```json curl theme={null}
{"upsertedCount":2}
```

`POST /vectors/upsert`

:::code-group
```bash title="cURL"
curl --request POST \
  --url https://{index_host}/vectors/upsert \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
  "vectors": [
    {
      "id": "example-vector-1",
      "values": [
        0.1,
        0.2,
        0.3,
        0.4,
        0.5,
        0.6,
        0.7,
        0.8
      ],
      "sparseValues": {
        "indices": [
          1,
          312,
          822,
          14,
          980
        ],
        "values": [
          0.1,
          0.2,
          0.3,
          0.4,
          0.5
        ]
      },
      "metadata": {
        "genre": "documentary",
        "year": 2019
      }
    }
  ],
  "namespace": "example-namespace"
}'
```

```json title="200"
{
  "upsertedCount": 2
}
```
:::

## Authorizations

- `Authorization` (header, string, required) — Bearer authentication header of the form `Bearer <token>`.

## Body

- `vectors` (body, object\[], required) — An array containing the vectors to upsert. Recommended batch limit is up to 1000 vectors.
- `namespace` (body, string) — The namespace where you upsert vectors.

## Response

- `200` — A successful response.
- `default` — An unexpected error response.

## Related pages

- [Search with a vector](./database-2026-07-data-plane-query.md)
- [Search with text](./database-2026-07-data-plane-search-records.md)
- [Upsert records](./database-2026-07-data-plane-upsert.md)
- [Upsert text](./database-2026-07-data-plane-upsert-records.md)
- [Fetch records](./database-2026-07-data-plane-fetch.md)
- [Fetch records by metadata](./database-2026-07-data-plane-fetch-by-metadata.md)
- [Update a record](./database-2026-07-data-plane-update.md)
- [Delete records](./database-2026-07-data-plane-delete.md)
- [List record IDs](./database-2026-07-data-plane-list.md)
- [Search with a vector](./database-2026-04-data-plane-query.md)

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